The Science Fiction Behind Search

The Science Fiction Behind Search

What used to be science fiction is now everyday reality in the world of search.
Here, Google Fellow Amit Singhal takes a moment to marvel at the incredible
capabilities search has brought us, and what we can expect in the future.

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As a boy in India, I dreamed of space. Watching episodes of Star Trek, I
was transported to the final frontier. I remember watching in wonder as Spock and
company beamed themselves to a mythical planet, used scanners to identify their
surroundings, and struck up conversations with aliens.

Now it’s my job to help make that science fiction come true, and we’re not doing
too badly. When search first captured my imagination two decades ago, the web was
sparsely populated with text, and data was achingly slow. But despite these
limitations, ‘surfing the web’ still felt like exploring space; discovering vast,
uncharted territories. Today we can voyage to the surface of Mars or the depths of
the ocean without ever leaving our couches, identify landmarks around the world
just by snapping a photo on our mobile phones, and have conversations with people
on the other side of the world, in dozens of languages we’ve never even studied.
And this is all thanks to incredible, you might even call them science
fiction-like, advancements in web and search technologies.

So where is search going? Let us first consider how our early science fiction
search dreams came to fruition.

Search_beyond_text

At Google, when we talk about organizing the world’s information, we don’t mean
only text; images and videos contain a wealth of information. In the early days,
this type of content simply didn’t exist online. Now, through efforts like Google
Earth and Street View, we can provide something incredibly valuable: images of your
physical world.

“Today we can voyage to the surface of Mars or the depths of the ocean without ever
leaving our couches.”

However, in many ways, getting visual information online is the easy part. What’s
hard is understanding that information. Unlike text, we cannot simply read an image
or video. We have to look inside them, dig out the pixels and translate them into
something meaningful. For a long time, we considered this a pipe dream, but by
combining search methodology and technological breakthroughs in computer vision,
today we can match pictures at a visual level. Search for “Mount Rushmore” on
Google and our algorithms will analyze many factors, such as the shape and texture
that produces a good image of Mount Rushmore, then return those images to you in
striking full-color. Better yet, take a picture of Mount Rushmore and Google
Goggles will recognize it and show relevant query results—no need to type at all.
(And if you don’t want to head to South Dakota, you can always recreate the
monument yourself.)

Search_beyond_language

Breaking down language barriers can unlock whole new worlds. Unfortunately,
engineers working on translation technologies quickly discovered that teaching a
computer to translate language is even more difficult than teaching a person.
Humans learn language by combining vocabulary with grammatical rules. But as we all
know, languages are complicated. There are exceptions to the rules, exceptions to
the exceptions, and exceptions to those exceptions. These exceptions, though
beautiful to humans, seem “illogical” to computers and result in poor translation
quality, making computer translations unusable. Plus, trying to teach these
exceptions to computers doesn’t scale well. To translate between every possible
language pair, whether it’s Japanese to Chinese, Hindi to Korean, or Urdu to
Swahili, your computer would have to learn a lot of exceptions.

So rather than trying to code lots of rules, we fed our translation engine
thousands of professionally translated documents and used statistical models to
identify patterns across them. These patterns helped us identify countless
correlations, and from those correlations, we can start predicting the best
translation for a given word, phrase or document. Today, Google Translate can help
you read search results, web pages, emails, YouTube video captions and more, in
over 50 languages. And that’s just for starters. Thanks to emerging voice
technology on mobile, you can even have a multilingual conversation with someone
face-to-face, in real-time, using speak-to-translate.

Search_that_knows_me

One of the most iconic science fiction images is the robotic butler who brings your
slippers, knows what temperature you like your tea, and anticipates your needs.
We’re certainly not there yet, but providing more personalized experiences is a
first step.

Everyone today has his or her very own version of Google. Your Google is different
from my Google, which is different from my neighbor’s version, and so on. This
makes a lot of sense, because we all have unique, distinct interests.

But building a tailored search engine for millions of users is no simple task, and
many factors influence which results will be most relevant to you at a given time.
For example, Google is localized across over 150 geographical domains, so when you
search for “pizza” in Tokyo, you’ll see pizza restaurants in your area. Sounds
simple, right? But things get exponentially more complicated with more
sophisticated users’ models.

Take the search query ‘lords’ for instance. This simple word means different things
to everyone: parliamentary houses, castles and swords, even a multiplayer online
game. However, as a fan of Indian cricket, I search for and click on
cricket-related things all the time. So when I search for “lords” on Google, I see
results about the Lord’s Cricket Ground, the most famous cricket field in London.

Results have also gotten a lot more personal and relevant thanks to Social Search,
which incorporates signals from people I’m connected to online. So, for example, I
might see a tweet from my friend about a recent game.

Search_the_present_moment

Just a short time ago, the vast majority of electronic information was locked away
in highly specialized databases with limited, often for-pay, access for research
purposes. From the time an article was written, it took months to index that
information in these specialized databases so that researchers could search for it.
The power of accessing data within seconds of when it was produced has transformed
us all, but for early search scientists, the concept of real-time search seemed
truly impossible.

Google launched Realtime Search—one of the most complicated projects I have ever
worked on—in December 2009. We developed a dozen new technologies to near-instantly
determine the relevance of these updates, from extracting information from
shortened URLs, to drawing meaning from shorthand conventions like “#obama,” to
evaluating changes in query volume to identify hot topics. The result: when
AT&T announced that it was interested in buying T-Mobile on March 20th, 2011,
Google’s Realtime Search started displaying tweets about the news several minutes
before major news organizations started reporting on the story.

Search with real-time results gets
people information faster, and it’s not a stretch to say that this can save lives.
Take Flu Trends: we use aggregated search data to estimate flu activity, providing
the information two weeks faster than CDC [Centers for Disease Control] data. The
implications of this are enormous.

Search_that_understands_me

We’ve started teaching computers how to translate languages, but teaching a
computer to actually understand language remains one of our biggest challenges.
Google knows that “GM” refers to General Motors in the context of cars, but
“genetically modified” in the context of food, for example. But what about words
with multiple meanings? How does Google know that when you’re looking to change the
brightness of your laptop screen, you actually want to “adjust” it? By contrast, if
you want to change a PDF file into a Word document, Google can help you learn how
to “convert” that file.

“If we can learn anything from history, it’s that science fiction doesn’t have to
stay that way.”

These may sound like straightforward substitutions, but remember: computers don’t
think like humans. Programming a computer to derive meaning from words and context
was barely imaginable some 20 years ago. And back then, what if we’d said that we
wanted to do this across all the world’s languages? We would have been called
crazy.

The holy grail of search is to understand what the user wants, not just matching
words, but actually trying to match meaning. Doing this before the user ever types
in a search query would be even better.

The_future_of_search

Every day, billions of documents get added to the web. People’s expectations are
changing. We want information delivered in all formats, in every language, tailored
to our personal preferences, and we want it NOW. Clearly, there is plenty of work
to be done to take search into the future, but in truth, we’ve come a long way in a
short time.

Just last year, we made over 500 improvements to search. But when you’re chasing
perfection, no matter how far you’ve come, no matter how many seemingly impossible
problems you solve, there is always more work to be done. In my mind, the holy
grail of search is to understand what the user wants, not just matching words, but
actually trying to match meaning. Doing this before the user ever types in a search
query would be even better.

Google Instant takes us down this road. Instant takes what you have typed already,
predicts the most likely completion and provides search results as you type,
yielding a smarter, faster search that is interactive, predictive and powerful.
Just ask Clay Shirky what we can do with all that extra time.

My dream search engine of the future guides me throughout the day. It knows my next
meeting is downtown, but the streets are closed, so I should take the subway. It
reminds me that my wife’s birthday is in two weeks, tells me she wants an iPad and
suggests I talk to my friend, Matt, who has done research on its Wi-Fi
capabilities. Then it sends me directions to the closest store. It could even
suggest a romantic restaurant nearby, search our schedules, and book a candlelit
table for two.

If we can learn anything from history, it’s that science fiction doesn’t have to
stay that way. We haven’t quite figured out how to beam you into space yet, but
then again, it’s still only 2011.